-
1.发明授权公开(公告)号：US09639779B2
公开(公告)日：2017-05-02
申请号：US14848583
申请日：2015-09-09
Applicant: KABUSHIKI KAISHA TOSHIBA
Inventor： Tatsuo Kozakaya , Tomokazu Kawahara , Susumu Kubota
CPC classification number: G06K9/6223 , G06K9/6256 , G06K9/6267
Abstract: According to an embodiment, a feature point detection device includes a generator to generate a K-class classifier and perform, for T times, an operation in which a first displacement vector is obtained that approximates D number of initial feature points of each training sample classified on a class-by-class basis to true feature points; a calculator to calculate, from the first displacement vectors, second displacement label vectors each unique to one second displacement vector, and a second displacement coordinate vector common to the second displacement vectors; a classifier to apply the K-class classifiers to the input image and obtain a second displacement label vector associated with a class identifier output from each K-class classifier; an adder to add up the second displacement label vectors; and a detector to detect D number of true feature points based on the initial feature points, the added label vector, and the second displacement coordinate vector.
-
2.发明申请CRACK DATA COLLECTION APPARATUS AND SERVER APPARATUS TO COLLECT CRACK DATA 审中-公开破裂数据收集装置和服务器装置收集裂纹数据
公开(公告)号：US20160133007A1
公开(公告)日：2016-05-12
申请号：US14850785
申请日：2015-09-10
Applicant: KABUSHIKI KAISHA TOSHIBA
Inventor： Takaaki Kuratate , Susumu Kubota , Norihiro Nakamura , Ryo Nakashima , Masaki Yamazaki , Akihito Seki
IPC: G06T7/00
CPC classification number: G06T7/12 , G06K9/48 , G06T7/001 , G06T2207/30108 , G06T2207/30132
Abstract: According to one embodiment, a crack data collection apparatus includes an acquisition unit, a detector, a calculator and a storage unit. The acquisition unit acquires an image obtained by photographing an inspection object region for a crack in a structure. The detector detects a crack pixel group included in the inspection object region from the image. The calculator successively sets turning points from a starting point to an end point on a contour of the crack pixel group, and calculates positions of the starting point, the turning points, and the end point and a vector of each of the points as crack data, The storage unit stores the crack data.
Abstract translation: 根据一个实施例，裂纹数据采集装置包括采集单元，检测器，计算器和存储单元。 获取单元获取通过拍摄结构中的裂纹的检查对象区域而获得的图像。 检测器从图像检测检查对象区域中包含的裂纹像素组。 计算机连续地设定从裂纹像素组的轮廓的起始点到终点的转折点，计算起点，转折点和终点的位置以及各点的向量作为裂纹数据 存储单元存储裂纹数据。
-
3.发明授权Image processing device, image processing method, and computer program product 有权图像处理装置，图像处理方法和计算机程序产品
公开(公告)号：US09237269B2
公开(公告)日：2016-01-12
申请号：US13937478
申请日：2013-07-09
Applicant: Kabushiki Kaisha Toshiba
Inventor： Toshiyuki Ono , Yasunori Taguchi , Takuma Yamamoto , Susumu Kubota , Nobuyuki Matsumoto
CPC classification number: H04N5/23212 , G06T5/002 , G06T5/50 , G06T2200/21 , G06T2207/10052 , H04N5/23232 , H04N13/282
Abstract: According to an embodiment, an image processing device includes a generator and a processor. The generator is configured to generate, from a plurality of unit images in which points on an object are imaged by an imaging unit at different positions according to distances between the imaging unit and the positions of the points on the object, a refocused image focused at a predetermined distance. The processor is configured to perform blurring processing on each pixel of the refocused image according to an intensity corresponding to a focusing degree of the pixel of the refocused image.
Abstract translation: 根据实施例，图像处理装置包括发生器和处理器。 发生器被配置为根据成像单元根据成像单元与对象上的点的位置之间的距离在不同位置处由成像单元对成像对象上的点进行成像的多个单位图像生成聚焦在 预定距离。 处理器被配置为根据对应于重聚焦图像的像素的聚焦度的强度对重聚焦图像的每个像素执行模糊处理。
-
公开(公告)号：US20210295014A1
公开(公告)日：2021-09-23
申请号：US17002601
申请日：2020-08-25
Applicant: KABUSHIKI KAISHA TOSHIBA
Inventor： Naoki Kawamura , Susumu Kubota
Abstract: According to an embodiment, a collation device includes a hardware processor configured to: generate, based at least in part on input data, an input vector comprising input data features indicating features of the input data, the input data features comprising D number of features, D being an integer equal to or larger than two; and
generate first specification information that specifies d selected features among the input data features of the input vector, based at least in part on a plurality of reference vectors and the input vector, the plurality of reference vectors each comprising reference features in the same form as the input vector, the reference features comprising the D number of features, d being an integer equal to or larger than one and smaller than D.
-
公开(公告)号：US09830363B2
公开(公告)日：2017-11-28
申请号：US15018986
申请日：2016-02-09
Applicant: KABUSHIKI KAISHA TOSHIBA
Inventor： Tomoki Watanabe , Susumu Kubota , Satoshi Ito , Tomohiro Nakai
CPC classification number: G06F17/3053 , G06F17/30256 , G06K9/4642
Abstract: According to an embodiment, an apparatus includes a calculator, an pixel evaluator, an accumulator, and an area evaluator. The calculator is configured to calculate a feature of an image for each pixel in image data. The pixel evaluator is configured to produce a score that evaluates the feature for each pixel. The accumulator is configured to calculate, for each pixel, a cumulative score obtained by accumulating all scores in an area including a minor angle formed by a half line in a first direction from the each pixel position and another half line in a second direction from the each pixel position. The area evaluator is configured to calculate an evaluation value that is a total of the scores in a quadrilateral area enclosed by two lines of the first direction and two lines of the second direction based on the cumulative scores at pixel positions at vertexes of the quadrilateral area.
-
6.发明授权
公开(公告)号：US09779062B2
公开(公告)日：2017-10-03
申请号：US14937566
申请日：2015-11-10
Applicant: Kabushiki Kaisha Toshiba
Inventor： Satoshi Ito , Susumu Kubota , Tomohiro Nakai
Abstract: According to an embodiment, a computing apparatus includes a memory, and a processor. The memory stores N first vectors in a d-dimensional binary vector space consisting of binary values. The processor acquires a second vector in the d-dimensional binary vector space. The processor extracts M first vectors having a distance from the second vector satisfying a first condition out of the N first vectors, and calculate a distribution of distances of the M first vectors from the second vector. The processor acquires a first kernel function per a first distance between the M first vectors and the second vector in a first range. The processor generates a second kernel function based on the distribution and the first kernel functions. The processor calculates an occurrence probability of the second vector in the N first vectors based on the second kernel function.
-
公开(公告)号：US20150363667A1
公开(公告)日：2015-12-17
申请号：US14721045
申请日：2015-05-26
Applicant: KABUSHIKI KAISHA TOSHIBA
Inventor： Tomohiro Nakai , Susumu Kubota , Satoshi Ito , Tomoki Watanabe
IPC: G06K9/62
CPC classification number: G06K9/6212 , G06K9/6256
Abstract: According to an embodiment, a recognition device includes a memory to store therein learning patterns each belonging to one of categories; an obtaining unit to obtain a recognition target pattern; a first calculating unit to calculate, for each category, a distance histogram representing distribution of the number of learning patterns belonging to the categories with respect to distances between the recognition target pattern and the learning patterns belonging to the categories; a second calculating unit to analyze the distance histogram of each category, and calculate a feature value of the recognition target pattern; a third calculating unit to make use of the feature value and one or more classifiers, and calculate degrees of reliability of the recognition target categories; and a determining unit to make use of the degrees of reliability and, from among the one or more recognition target categories, determine a category of the recognition target pattern.
Abstract translation: 根据实施例，识别装置包括：存储器，用于存储各自属于类别之一的学习模式; 获取单元以获得识别目标图案; 第一计算单元，对于每个类别，计算表示属于所述类别的学习图案数量相对于属于所述类别的所述学习图案之间的距离的分布的距离直方图; 第二计算单元，用于分析每个类别的距离直方图，并计算识别目标图案的特征值; 第三计算单元，用于利用特征值和一个或多个分类器，并计算识别目标类别的可靠度; 以及确定单元，以利用所述可靠性程度，并且从所述一个或多个识别目标类别中确定所述识别目标图案的类别。
-
8.发明申请
公开(公告)号：US20200159743A1
公开(公告)日：2020-05-21
申请号：US16548113
申请日：2019-08-22
Applicant: KABUSHIKI KAISHA TOSHIBA
Inventor： Satoshi Ito , Tatsuo Kozakaya , Yuta Shirakawa , Susumu Kubota
Abstract: An information processing device according to one embodiment includes a first receiver, a second receiver, a first converter, a second converter, and a calculator. The first receiver receives input of first data belonging to a first modality. The second receiver receives input of second data belonging to a second modality that is different from the first modality. The first converter converts the first data into a first representation representing a point or a first area in a D-dimensional vector space (D is a natural number). The second converter converts the second data into a second representation representing a second area in the D-dimensional vector space. The calculator calculates similarity between the first data and the second data by using the first representation and the second representation.
-
公开(公告)号：US09390347B2
公开(公告)日：2016-07-12
申请号：US14132371
申请日：2013-12-18
Applicant: KABUSHIKI KAISHA TOSHIBA
Inventor： Tomohiro Nakai , Susumu Kubota , Satoshi Ito
IPC: G06K9/62
CPC classification number: G06K9/627
Abstract: A recognition device includes a storage unit, an acquiring unit, a first calculator, a second calculator, a determining unit, and an output unit. The storage unit stores multiple training patterns each belonging to any one of multiple categories. The acquiring unit acquires a recognition target pattern to be recognized. The first calculator calculates, for each of the categories, a distance histogram representing distribution of the number of training patterns belonging to the category with respect to distances between the recognition target pattern and the training patterns belonging to the category. The second calculator analyzes the distance histogram of each of the categories to calculate confidence of the category. The determining unit determines a category of the recognition target pattern from the multiple categories by using the confidences. The output unit outputs the category of the recognition target pattern.
Abstract translation: 识别装置包括存储单元，获取单元，第一计算器，第二计算器，确定单元和输出单元。 存储单元存储多个属于多个类别中的任何一个的训练模式。 获取单元获取要识别的识别目标图案。 第一计算器针对每个类别，计算表示属于该类别的训练模式的数量相对于属于该类别的识别目标模式与训练模式之间的距离的分布的距离直方图。 第二个计算器分析每个类别的距离直方图以计算类别的置信度。 确定单元通过使用信任从多个类别确定识别目标模式的类别。 输出单元输出识别目标图案的类别。
-
公开(公告)号：US20160133008A1
公开(公告)日：2016-05-12
申请号：US14850803
申请日：2015-09-10
Applicant: KABUSHIKI KAISHA TOSHIBA
Inventor： Takaaki Kuratate , Susumu Kubota , Norihiro Nakamura , Ryo Nakashima , Masaki Yamazaki , Akihito Seki
IPC: G06T7/00
CPC classification number: G06T7/001 , G06K9/48 , G06T7/12 , G06T2207/30108 , G06T2207/30132
Abstract: According to one embodiment, a crack data collection method includes acquiring an image obtained by photographing an inspection object region for a crack in a structure, detecting a crack pixel group included in the inspection object region from the image, successively setting turning points from a starting point to an end point on a contour of the crack pixel group, and analyzing and collecting positions of the starting point, the turning points, and the end point and a vector of each of the points, as crack data.
Abstract translation: 根据一个实施例，裂纹数据收集方法包括获取通过拍摄结构中的裂纹的检查对象区域获得的图像，从图像中检测检查对象区域中包括的裂纹像素组，从起始开始依次设定转折点 指向裂纹像素组的轮廓上的终点，并分析和收集起点，转折点和终点的位置以及每个点的向量作为裂纹数据。
